Real‐time Anticipation of Occlusions for Automated Camera Control in Toric Space

Abstract

AbstractEfficient visibility computation is a prominent requirement when designing automated camera control techniques for dynamic 3D environments; computer games, interactive storytelling or 3D media applications all need to track 3D entities while ensuring their visibility and delivering a smooth cinematic experience. Addressing this problem requires to sample a large set of potential camera positions and estimate visibility for each of them, which in practice is intractable despite the efficiency of ray‐casting techniques on recent platforms. In this work, we introduce a novel GPU‐rendering technique to efficiently compute occlusions of tracked targets in Toric Space coordinates – a parametric space designed for cinematic camera control. We then rely on this occlusion evaluation to derive an anticipation map predicting occlusions for a continuous set of cameras over a user‐defined time window. We finally design a camera motion strategy exploiting this anticipation map to minimize the occlusions of tracked entities over time. The key features of our approach are demonstrated through comparison with traditionally used ray‐casting on benchmark scenes, and through an integration in multiple game‐like 3D scenes with heavy, sparse and dense occluders.